Field of the Invention
Embodiments of the invention relate to hydrocarbon reservoir production and, more specifically, to methods, systems, and non-transitory computer-readable medium having computer program stored therein to enhance hydrocarbon reservoir simulation for a plurality of hydrocarbon reservoirs.
Background of the Invention
Hydrocarbon reservoir simulation models may be constructed to provide information related to fluid flow and other features within real hydrocarbon reservoirs. Simulations of fluid flow, for example, may then be performed on the models. In some circumstances, multiple simulation runs may be performed on a single hydrocarbon reservoir simulation model. Among other advantages, performing multiple simulation runs may, for example, increase confidence in the results of the simulation runs and thereby increase the value of the results during analysis of the hydrocarbon reservoir. A simulation run is typically scheduled to run for one or more time steps—defined periods of time—as understood by those of skill in the art. Multiple simulation runs performed as part of the same project may sometimes be described collectively as a simulation study.
Hydrocarbon reservoir simulation may include both user interaction 51 and simulator action 52, as illustrated in FIG. 2a, for example. User interaction 51, for example, may include loading and investigating historical data related to the subject hydrocarbon reservoir 53. Historical data may include, for example, actual measured data related to the hydrocarbon reservoir, i.e., measurements and observations collected during exploration of and production from the hydrocarbon reservoir. Simulator action 52 may then take control of the hydrocarbon reservoir simulation process. For example, simulator action 52 may include starting a simulation run 54, outputting time step data 55 for a time step of the simulation run to produce time step data 56, and determining whether the time step was the last time step to be performed 57. If the time step was not the last time step to be performed 57, simulator action 52 may then include continuing the simulation run 58 for another time step and subsequently outputting time step data 55. If the time step was the last time step to be performed 57, however, simulator action 52 may then include wrapping up the simulation run 59 to produce output data 60. Simulator action may then include determining whether the simulator has more simulation runs (sometimes called “simulation cases” or “simulation jobs”) to perform 61. If so, simulator action 52 may then include picking the next simulation run 62 then starting that simulation run 54. If the simulator does not have any more simulation runs to perform 61, it may complete the simulation process 63.
Hydrocarbon reservoir simulation may include at least two important types of simulations of fluid flow in a hydrocarbon reservoir: (1) history-matching simulations and (2) prediction (or predictive) simulations. History-matching simulations may serve to validate a model of the subject hydrocarbon reservoir by producing a variety of simulated hydrocarbon fluid flow data. That simulated hydrocarbon fluid flow data may then be compared to historical, observed data from the real hydrocarbon reservoir. That is, history-matching simulations may calibrate a hydrocarbon reservoir model to minimize any mismatch between the model and the reservoir and to build confidence in the model. Prediction simulations, on the other hand, may produce data related to predicted future hydrocarbon fluid flow. That is, engineers may use prediction simulations to answer questions of what will happen under different possible development scenarios. In some circumstances, prediction simulations may be part of an optimization problem, and a simulation engineer may perform multiple simulation runs with outcomes in a valid solution space to select the simulation run most closely aligned with a development goal. Multiple prediction simulation runs may therefore be used to fine tune development strategies to achieve objectives related to development of a hydrocarbon reservoir, for example. Higher quality hydrocarbon reservoir simulation models may be desirable because they may produce more accurate predictions. Notably, history-matching simulations may affect prediction simulations, though, because history-matching simulations may be used to improve the quality of a hydrocarbon reservoir simulation model later used for prediction simulations. Consequently, history matching may be an important part of hydrocarbon reservoir simulation.
Further, history matching is an optimization problem. One of the main objectives of history matching, for example, may be to validate a numerical hydrocarbon reservoir simulation model by minimizing the differences between the numerical solution—the simulator output—and field historical pressure, production, and injection data. This validation process may lead to better management and quantification of uncertainties in a simulation model. Ultimately, the history-matched numerical model may be used for prediction studies and hydrocarbon field development evaluations. FIG. 2b illustrates an example history-matching method according to the prior art. As illustrated in FIG. 2b, for example, a geological model 71 may be upscaled 72 to a simulation model 73. A fluid flow simulation 74 may then be performed. Using production data 75, whether an objective function has been met may be determined 76. An objective function of a simulation study may be the objective, i.e., the goal, of the study in terms of output. An objective function of a prediction study, for instance, may be to maximize oil production, in some circumstances. As another example, an objective function of a history-matching study may be to develop a hydrocarbon reservoir simulation model that closely approximates the characteristics of the real hydrocarbon reservoir it models. Consequently, an objective function may relate to the difference between simulation output data—output of a fluid flow simulation 74, i.e., fluid flow simulation results—and production data 75, for example. More specifically, an objective function may be used to determine whether an acceptable match has been reached between fluid flow simulation results and historical, observed data, i.e., actual measured data. Furthermore, a match may be determined based on some predefined acceptance criteria. An objective function determination may be “yes” when an acceptable match has been reached, e.g., when the difference between the output of a fluid flow simulation 74 and production data 75 is below a preselected level. Conversely, an objective function determination may be “no” when the difference between the output of a fluid flow simulation 74 and production data 75 is above a preselected level, for example. As depicted in FIG. 2b, for instance, if the objective function has been met 76, the method may stop 78. If the objective function has not been met 76, manual optimization 77 may occur and feed back into the simulation model 73.
In contrast to manual history-matching processes, Assisted History Matching (AHM) automates the optimization process using state-of-the-art, proven optimization algorithms. AHM is a class of simulation problems that allows reservoir simulation engineers to change many parameters simultaneously, automate processes, and be able to better document different history-matching scenarios. A history-matching process using AHM is illustrated, for example, in FIG. 2c. As illustrated in FIG. 2c, for example, a geological model 81 may be upscaled 82 to produce a simulation model 83. A fluid flow simulation 84 may then be performed on the simulation model 83. Then, using production data 85 as input, whether an objective function has been met may be determined 86. If the objective function has been met 86, the process may stop 88. If the objective function has not been met 86, an assisted optimization process 87 may begin and feed back into the geological model 81.